Role OverviewSuperDial is building AI agents that do real work inside healthcare revenue cycle operations. Our agents help customers automate high-volume workflows such as claims status follow-up, eligibility, benefits verification, prior authorization, and payer communications.
We recently closed our Series B and are entering an exciting stage of company and product growth. As we expand from outbound payer calls into more advanced workflow automation, multimodal evidence gathering, and inbound agent experiences, we are looking for an Associate Product Manager to help us build, test, launch, and improve AI agent products in production.
In this role, you will report to the VP of Product and work closely with Product, Engineering, Operations, Customer Success, and Sales. You will support product execution across AI agent workflows by helping define requirements, organize customer and operational feedback, test product behavior, track agent performance, and create clear documentation for internal teams.
This is a strong fit for an early-career product builder who is technically curious, highly organized, customer-centered, and excited to learn how applied AI can solve real operational problems in healthcare.
What You'll Do- Own the development and improvement of AI agent workflows across areas such as outbound voice, workflow automation, evidence gathering, and inbound agent experiences.
- Partner with Product and Engineering to write clear requirements, user stories, acceptance criteria, product notes, and launch materials.
- Advance SuperDial's core healthcare revenue cycle workflows and help translate operational complexity into clear product inputs.
- Review customer feedback, operational escalations, product data, and agent outputs to identify patterns and surface improvement opportunities.
- Contribute to QA and launch readiness, including test cases, edge-case review, issue tracking, internal documentation, and post-launch monitoring.
- Evaluate agent performance across workflow completion, reliability, escalation patterns, and customer impact.
- Partner with Operations and Customer Success to understand where product behavior is working well, where it breaks down, and what needs to improve.
- Support customer pilots by organizing feedback, tracking open questions, and helping determine what is ready to scale.
- Create internal documentation, workflow guides, enablement materials, and release notes that make product behavior easier to understand across teams.
- Contribute to repeatable product and operating patterns that help SuperDial deploy AI agents more consistently across customers.
Who You Are- Technically curious: You are excited by applied AI, automation, and workflow software. You want to understand how AI agents behave in real customer environments.
- Detail-oriented: You are comfortable working through workflows, edge cases, tickets, data inputs, QA steps, and customer-specific requirements.
- Customer-centered: You care about how users and operators actually work and can turn customer pain points into useful product inputs.
- Analytical: You are comfortable using data, examples, and patterns to understand problems and recommend practical next steps.
- Organized and reliable: You can manage multiple inputs, follow up consistently, and help keep cross-functional work moving.
- Clear communicator: You write clearly, structure information well, and help teams stay aligned.
- Eager to learn: You are excited to grow in product management, applied AI, and healthcare technology through hands-on execution.
What We're Looking For- 4+ years of experience in product management, product operations, implementation, solutions, technical operations, customer operations, data operations, or a similarly analytical and cross-functional role, with demonstrated ownership of complex product or workflow initiatives.
- Experience owning or meaningfully contributing to product discovery, requirements definition, prioritization, delivery, launch, and post-launch iteration for a product, workflow, or customer-facing capability.
- Has helped bring a product or product capability to market, including defining launch requirements, enabling customer-facing teams, gathering post-launch feedback, and using customer or commercial insights to inform product priorities.
- Strong product judgment, including the ability to synthesize customer needs, operational realities, technical constraints, and business priorities into clear recommendations and execution plans.
- Ability to quickly learn complex workflows and translate ambiguous customer, operational, or technical inputs into clear requirements, success criteria, documentation, and next steps.
- Comfort working closely with Engineering, Operations, Customer Success, Sales, and leadership to understand product behavior, customer requirements, production issues, edge cases, and opportunities for improvement.
- Excellent organization and attention to detail, with the ability to manage multiple inputs and follow up reliably.
- Strong analytical instincts, including comfort using data, customer examples, product performance, and qualitative feedback to understand problems, evaluate tradeoffs, and recommend next steps.
- Clear written and verbal communication, with the ability to create alignment, document decisions, and drive follow-through across cross-functional teams.
- Strong interest in applied AI, automation, healthcare technology, workflow software, or technically complex products.
Bonus Points- Experience working on AI, automation, workflow, data-heavy, or technically complex software products.
- Exposure to healthcare revenue cycle management, payer/provider workflows, claims status, eligibility, prior authorization, denials, billing operations, or RCM services.
- Experience supporting QA, customer pilots, implementation, or post-launch monitoring.
- Familiarity with integrations, APIs, CSV/data ingestion, dashboards, logs, or customer-specific workflow configuration.
- Ability to read basic SQL or use AI-assisted tools to explore product behavior.
- Experience creating product documentation, enablement materials, workflow playbooks, release notes, or internal operating guides.
- Exposure to GCP tools such as BigQuery, Vertex AI, Cloud Functions, Cloud Run, Pub/Sub, or related data and AI infrastructure.
